1. Field of the Invention
This invention relates to a prospective abnormal shadow detecting system for detecting a prospective abnormal shadow in a radiation image, and more particularly to a prospective abnormal shadow detecting system for detecting a micro calcification area, in which a prospective shadow of micro calcification exists, on the basis of radiation image data of an object and to a prospective abnormal shadow detecting system for detecting a benignant micro calcification area, in which a prospective shadow of benignant micro calcification exists, and a malignant micro calcification area, in which a prospective shadow of malignant micro calcification exists, separately from each other on the basis of radiation image data of an object.
2. Description of the Related Art
In the medical field, to find a diseased part of a patient or to observe a diseased part of a patient and diagnose progress of disease by reading a radiation image of the object (patient) has been a common operation. However, radiation image reading often depends upon experience and abilities of the reader and is not necessarily objective.
For example, it is necessary to find an abnormal shadow representing a growth and/or a micro calcification representative of a cancerous part in a mammogram (a radiation image of a breast) taken for the purpose of a breast cancer examination. However, depending on the reader, the abnormal shadow area cannot be properly designated. Accordingly, there has been a demand to properly detect an abnormal shadow including shadows of a growth and a micro calcification.
In order to meet this demand, a prospective abnormal shadow detecting system (a computer-aided image diagnosis system), has been proposed, as disclosed, for instance, in Japanese Unexamined Patent Publication Nos. 8(1996)-294479 and 8(1996)-287230 in which a prospective abnormal shadow is automatically detected by the use of a computer on the basis of image data representing a radiation image of the object. In the prospective abnormal shadow detecting system, a prospective abnormal shadow is automatically detected on the basis of density distribution and/or configurational feature by the use of an iris filter processing which is mainly suitable for detecting a growth shadow or a morphology filter processing which is mainly suitable for detecting a prospective micro calcification shadow.
The morphology filter processing is a method effective to detect a shadow of prospective micro calcification (comprising a plurality of small calcified areas), which is a specific form of breast cancer, by comparing a predetermined threshold value with the output value of a morphology operation using a structural element which is larger in size than micro calcification to be detected. The morphology filter processing will be described in detail, hereinbelow.
The morphology filter is a filter which can remove from an image noises and/or shadows which are smaller in size than a structural element employed and is generally used for smoothening an image signal, extraction of a shadow of prospective micro calcification, and the like.
(The Fundamentals of Morphology Operation)
Though the morphology operation is generally developed as a set theory in a N-dimensional space, it will be discussed here on the basis of a two-dimensional tone image for the purpose of simplicity of understanding.
It is assumed that a tone image is a space in which a point (x, y) has a height corresponding to a value of density f(x, y). Further it is assumed that the value of density f(x, y) is represented by a high brightness, high level signal in which as the value of density decreases (the value of brightness increases when displayed on a CRT), the level of the signal becomes higher.
For the purpose of simplicity, a linear function f(x) corresponding to a cross-section of the image is first discussed. It is assumed that a structural element g employed in the morphology operation is a function which is represented by the following formula (1), is symmetrical about the origin, and is 0 in value in a domain represented by the following formula (2).gs(x)=g(−x)  (1)G={−m, −m+1, . . . , −1, 0, 1, . . . , m−1, m}  (2)
At this time, the fundamental form of the morphology operation is very simple as shown in the following formulae (3) to (6).dilation: [f⊕Gs](i)=max{f(i−m), . . . , f(i), . . . , f(i+m)}  (3)erosion: [f⊖Gs](i)=min{f(i−m), . . . , f(i), . . . , f(i+m)}  (4)opening: fg=(f⊖gs)⊕g  (5)closing: fg=(f⊕gs)⊖g  (6)
That is, the dilation processing is processing for searching a maximum value in the area whose width is ±m (a value determined according to the structural element B) and whose center is at the pixel of current interest, see FIG. 4A, and the erosion processing is processing for searching a minimum value in the same area, see FIG. 4B. The opening processing corresponds to searching a maximum value after searching a minimum value, and the closing processing corresponds to searching a minimum value after searching a maximum value. In other words, the opening processing corresponds to smoothening the density curve f(x) from the low brightness side and removing protrusions in density (the portions which are higher in brightness than the surroundings) which are narrower than the mask size 2 m (see FIG. 4C), whereas the closing processing corresponds to smoothening the density curve f(x) from the high brightness side and removing recesses in density (the portions which are lower in brightness than the surroundings) which are narrower than the mask size 2 m (see FIG. 4D).
In the case of a high density, high level signal in which as the value of density increases, the level of the signal becomes higher, the value of image signal for the value of density f(x) is reverse to that of a high brightness, high level signal. Accordingly, the dilation processing for a high density, high level signal corresponds to the erosion processing for a high brightness, high level signal. Similarly, the erosion processing for a high density, high level signal corresponds to the dilation processing for a high brightness, high level signal, the opening processing for a high density, high level signal corresponds to the closing processing for a high brightness, high level signal, and the closing processing for a high density, high level signal corresponds to the opening processing for a high brightness, high level signal. Description will be made only on the high brightness, high level signal here.
(Application to Detection of a Micro Calcification Shadow)
As a method of detecting a micro calcification shadow, a subtraction method in which a smoothened image is subtracted from an original image is conceivable. Since it is difficult to distinguish a calcification shadow from an elongated non-calcification shadow (e.g., of a mammary gland, a blood vessel, and a mammary gland supporting tissue) by a simple smoothening method, morphology operation processing based on opening operation using multiple structural elements as represented by the following formula (7) has been proposed. See “Extraction of Microcalcifications on Mammogram Using Morphological Filter with Multiple Structuring Elements” (Journal of Academy of Electronics/Information/Communication D-II, vol. J75-D-II No. 7, pp. 1170 to 1176, July 1992) and “Basic Theory of Mathematical Morphology and its Application to Mammograms Processing” (MEDICAL IMAGING TECHNOLOGY, Vol. 12, No. 1 January 1994).
                                                        P              =                            ⁢                              f                -                                                      max                                          i                      ∈                                              (                                                  1                          ,                          ⋯                          ,                          M                                                )                                                                              ⁢                                      {                                                                  (                                                  f                          ⊖                          Bi                                                )                                            ⊕                      Bi                                        }                                                                                                                          =                            ⁢                              f                -                                                      max                                          i                      ∈                                              (                                                  1                          ,                          ⋯                          ,                          M                                                )                                                                              ⁢                                      {                                          f                      Bi                                        }                                                                                                          (        7        )            wherein Bi (i stands for 1, 2, 3 and 4) are four linear structural elements B shown in FIG. 5. When the structural elements B are larger than calcification shadows to be detected, calcification shadows which are protrusions in the image signal narrower than the structural elements B (a part of the image the image signal of which fluctuates in a range spatially narrower than the structural elements B) are removed by opening processing. On the other hand, an elongated non-calcification shadow is left there as it is after the opening processing (calculation of the second term in formula 7) so long as it is longer than the structural elements B and its inclination (the direction in which the shadow extends) conforms to any one of the four structural elements Bi. Accordingly, by subtracting the smoothened image (the image removed with the calcification shadow) obtained by the opening processing from the original image f, an image containing therein only a small prospective calcification shadow is obtained. This the concept of formula (7).
In the case of a high density, high level signal, closing processing is applied according to the following formula (8) in place of the opening processing represented by formula (7).
                                                        P              =                            ⁢                              f                -                                                      min                                          i                      ∈                                              (                                                  1                          ,                          ⋯                          ,                          M                                                )                                                                              ⁢                                      {                                                                  (                                                  f                          ⊕                          Bi                                                )                                            ⊖                      Bi                                        }                                                                                                                          =                            ⁢                              f                -                                                      min                                          i                      ∈                                              (                                                  1                          ,                          ⋯                          ,                          M                                                )                                                                              ⁢                                      {                                          f                      Bi                                        }                                                                                                          (        8        )            
However, a non-calcification shadow equivalent to a calcification shadow in size can still remain. In such a case, non-calcification shadows contained in P represented by formula (7) are further removed by the use of differential information based on a morphology operation according to the following formula (9).Mgrad=(½)×{f⊕λB−f⊖λB}  (9)
As the value of Mgrad increases, the probability that the shadow is of a micro calcification increases. Accordingly, a prospective micro calcification shadow Cs can be obtained according to the following formula (10).If P(i, j)≧T1, and Mgrad(i, j)≧T2Then, Cs(i, j)=P else Cs(i, j)=0  (10)T1 and T2 are empirically determined threshold values.
Since a non-calcification shadow different from a calcification shadow in size can be removed only by comparison of P obtained according to formula (7) and the threshold value T1, only the condition of the first term of formula (10), P(i, j)≧T1 has to be satisfied in the case where there is no possibility that a non-calcification shadow equivalent to a calcification shadow in size remains.
Finally, the cluster area Cc of the micro calcification shadow (the area in which the micro calcification exists) is detected by a combination of a multi-scale opening operation and closing operation represented by the following formula (11).Cc=Cs⊕λ1B⊖λ3B⊕λ2B  (11)wherein λ1 and λ2 are respectively determined by the maximum distance between calcification shadows to be fused and the maximum radius of an isolated shadow to be removed, and λ3=λ1+λ2.
Though the morphology operation processing has been described in conjunction with a high brightness, high level signal, the relation between the opening processing and the closing processing is reversed in the case of a high density, high level signal in which a pixel of a higher density has a larger digital value.
It is necessary to set larger the threshold values T1 and T2 in order to surely remove non-calcification shadows smaller than micro calcification shadows from the image Cs including therein a prospective micro calcification shadow. However when the threshold values T1 and T2 are set larger, there arises fear that a thin prospective micro calcification shadow (a shadow of micro calcification low in density) can be regarded as of noise and removed. To the contrast, when the threshold values T1 and T2 are set smaller, the image obtained will include a lot of noise though a thin prospective micro calcification shadow can be extracted as a prospective micro calcification shadow, and accordingly, when a prospective micro calcification area is detected on the basis of such an image, there is fear that the detecting accuracy deteriorates.
Further, when the threshold values T1 and T2 are set large so that a prospective micro calcification image including substantially no non-calcification shadow like noise can be obtained and a prospective micro calcification area is detected on the basis of the prospective micro calcification image, it is preferred that attributes of the prospective micro calcification area (e.g., whether it is malignant or benignant) or other information useful for diagnosis be provided to the shadow reader together with the result of the detection in order to better aid in diagnosis.